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<h1 class="reftitle">evaluate</h1>
<h2>Purpose</h2>
<p>Returns the optimal control action</p>
<h2>Syntax</h2>
<pre class="synopsis">u = controller.evaluate(x0)</pre>
<pre class="synopsis">[u, feasible] = controller.evaluate(x0)</pre>
<pre class="synopsis">[U, feasible, openloop] = controller.evaluate(x0)</pre>
<h2>Description</h2>
<p></p> 
    
      <tt>u = controller.evaluate(x0)</tt> solves the MPC optimization
	problem using <tt>x0</tt> as the initial condition and returns the
	first element of the optimal sequence of control inputs. If
	the problem is infeasible, <tt>u</tt> will be <tt>NaN</tt>.<br><br>

    
      <tt>[u, feasible] = controller.evaluate(x0)</tt> also returns the
	boolean feasibility flag.<br><br>

    
      <tt>[u, feasible, openloop] = controller.evaluate(x0)</tt> also returns
	the open-loop predictions of states, inputs and outputs in 
	<tt>openloop.X</tt>, <tt>openloop.Y</tt>, and <tt>openloop.Y</tt>,
	respectively. Value of the optimal cost is returned in
	<tt>openloop.cost</tt>.
  <h2>Input Arguments</h2>
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<td><tt>x0</tt></td>
<td>
<p></p>Initial state of the MPC optimization problem.<p>
	    		Class: <tt>double</tt></p>
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<h2>Output Arguments</h2>
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<td><tt>u</tt></td>
<td>
<p></p>Optimal control action.<p>
	    		Class: <tt>double</tt></p>
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<td><tt>feasible</tt></td>
<td>
<p></p>True if the optimization problem was feasible, false otherwise.<p>
	    		Class: <tt>logical</tt></p>
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<td><tt>openloop</tt></td>
<td>
<p></p>Structure containing open-loop predictions and value of the optimal cost.<p>
	    		Class: <tt>struct</tt></p>
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<br><p>©  <b>2003-2013</b>     Michal Kvasnica: STU Bratislava,    <a href="mailto:michal.kvasnica@stuba.sk">michal.kvasnica@stuba.sk</a></p>
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